sparse_bw_api.yaml

- backward_api : conv3d_grad
  forward : conv3d (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm) -> Tensor(out@SparseCooTensor), Tensor(rulebook@DenseTensor)
  args : (Tensor x, Tensor kernel, Tensor rulebook, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm)
  output : Tensor(x_grad@SparseCooTensor), Tensor(kernel_grad@DenseTensor)
  kernel :
    func : sparse_conv3d_grad

- backward_api : coo_to_dense_grad
  forward : coo_to_dense(Tensor x) -> Tensor(out@DenseTensor)
  args : (Tensor x, Tensor out_grad)
  output : Tensor(x_grad@SparseCooTensor)
  kernel :
    func : sparse_coo_to_dense_grad

- backward_api : coo_values_grad
  forward : coo_values(Tensor x) -> Tensor(out@DenseTensor)
  args : (Tensor x, Tensor out_grad)
  output : Tensor(x_grad@SparseCooTensor)
  kernel :
    func : coo_values_grad

- backward_api : create_sparse_coo_tensor_grad
  forward : create_sparse_coo_tensor(Tensor values, Tensor indices, IntArray dense_shape) -> Tensor(out@SparseCooTensor)
  args : (Tensor indices, Tensor out_grad)
  output : Tensor(values_grad@DenseTensor)
  kernel :
    func : sparse_coo_tensor_grad

- backward_api : dense_to_coo_grad
  forward : dense_to_coo(Tensor x, int64_t sparse_dim) -> Tensor(out@SparseCooTensor)
  args : (Tensor out_grad)
  output : Tensor(x_grad@DenseTensor)
  invoke : to_dense_impl(out_grad)

- backward_api : sparse_maxpool_grad
  forward : sparse_maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out@SparseCooTensor), Tensor(rulebook@DenseTensor)
  args : (Tensor x, Tensor rulebook, Tensor out, Tensor out_grad, int[] kernel_sizes)
  output : Tensor(x_grad@SparseCooTensor)
  kernel :
    func : sparse_maxpool_grad

- backward_api : sparse_relu_grad
  forward : sparse_relu(Tensor x) -> Tensor(out@SparseCooTensor)
  args : (Tensor x, Tensor out_grad)
  output : Tensor(x_grad@SparseCooTensor)
  kernel :
    func : sparse_relu_grad